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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2025-07-08, 18:19 CEST based on data in:
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605259_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605260_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605261_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605262_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605263_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605264_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605265_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605266_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605267_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605268_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605269_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605270_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605271_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605272_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605273_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605274_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605259_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605260_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605261_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605262_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605263_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605264_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605265_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605266_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605267_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605268_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605269_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605270_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605271_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605272_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605273_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605274_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605259_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605260_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605261_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605262_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605263_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605264_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605265_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605266_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605267_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605268_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605269_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605270_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605271_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605272_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605273_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605274_kneaddata_paired_1_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605259_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605260_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605261_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605262_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605263_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605264_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605265_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605266_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605267_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605268_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605269_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605270_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605271_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605272_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605273_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kneaddata/fastqc/SRR11605274_kneaddata_paired_2_fastqc.zip
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605259.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605260.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605261.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605262.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605263.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605264.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605265.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605266.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605267.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605268.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605269.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605270.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605271.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605272.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605273.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/kraken2/SRR11605274.kraken2_report.txt
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605259.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605260.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605261.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605262.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605263.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605264.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605265.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605266.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605267.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605268.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605269.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605270.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605271.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605272.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605273.bracken
        • /crex/proj/uppstore2017185/b2014034_nobackup/Dasha/AIT_meta/results/bracken/SRR11605274.bracken

        General Statistics

        Showing 80/80 rows and 6/9 columns.
        Sample NameStreptococcus thermophilusTop 5 speciesUnclassifiedDupsGCAvg lenMedian lenFailedSeqs
        SRR11605259
        93.1%
        93.1%
        0.6%
        SRR11605259_1
        65.4%
        39.0%
        150bp
        150bp
        20%
        7.3M
        SRR11605259_2
        62.6%
        39.0%
        150bp
        150bp
        20%
        7.3M
        SRR11605259_kneaddata_paired_1
        66.1%
        39.0%
        149bp
        150bp
        20%
        7.0M
        SRR11605259_kneaddata_paired_2
        64.0%
        39.0%
        148bp
        150bp
        20%
        7.0M
        SRR11605260
        84.1%
        84.1%
        0.6%
        SRR11605260_1
        62.7%
        39.0%
        150bp
        150bp
        20%
        7.9M
        SRR11605260_2
        60.5%
        39.0%
        150bp
        150bp
        20%
        7.9M
        SRR11605260_kneaddata_paired_1
        63.2%
        40.0%
        149bp
        150bp
        20%
        7.6M
        SRR11605260_kneaddata_paired_2
        61.7%
        40.0%
        148bp
        150bp
        20%
        7.6M
        SRR11605261
        94.0%
        94.0%
        0.5%
        SRR11605261_1
        66.9%
        39.0%
        150bp
        150bp
        20%
        6.5M
        SRR11605261_2
        65.4%
        39.0%
        150bp
        150bp
        20%
        6.5M
        SRR11605261_kneaddata_paired_1
        67.7%
        39.0%
        149bp
        150bp
        20%
        6.2M
        SRR11605261_kneaddata_paired_2
        66.5%
        39.0%
        149bp
        150bp
        20%
        6.2M
        SRR11605262
        0.0%
        0.1%
        72.5%
        SRR11605262_1
        46.1%
        37.0%
        150bp
        150bp
        10%
        5.7M
        SRR11605262_2
        45.1%
        37.0%
        150bp
        150bp
        10%
        5.7M
        SRR11605262_kneaddata_paired_1
        46.0%
        37.0%
        148bp
        150bp
        10%
        5.4M
        SRR11605262_kneaddata_paired_2
        45.4%
        37.0%
        148bp
        150bp
        10%
        5.4M
        SRR11605263
        0.0%
        54.1%
        0.5%
        SRR11605263_1
        47.9%
        48.0%
        150bp
        150bp
        10%
        7.8M
        SRR11605263_2
        47.2%
        48.0%
        150bp
        150bp
        10%
        7.8M
        SRR11605263_kneaddata_paired_1
        48.1%
        48.0%
        149bp
        150bp
        10%
        7.5M
        SRR11605263_kneaddata_paired_2
        47.7%
        48.0%
        149bp
        150bp
        10%
        7.5M
        SRR11605264
        92.9%
        92.9%
        1.0%
        SRR11605264_1
        69.5%
        38.0%
        150bp
        150bp
        20%
        9.5M
        SRR11605264_2
        66.8%
        38.0%
        150bp
        150bp
        20%
        9.5M
        SRR11605264_kneaddata_paired_1
        70.4%
        38.0%
        148bp
        150bp
        20%
        9.0M
        SRR11605264_kneaddata_paired_2
        68.3%
        38.0%
        148bp
        150bp
        20%
        9.0M
        SRR11605265
        93.1%
        93.1%
        1.3%
        SRR11605265_1
        71.1%
        35.0%
        150bp
        150bp
        20%
        6.2M
        SRR11605265_2
        66.3%
        35.0%
        150bp
        150bp
        20%
        6.2M
        SRR11605265_kneaddata_paired_1
        71.9%
        35.0%
        149bp
        150bp
        20%
        5.7M
        SRR11605265_kneaddata_paired_2
        69.3%
        35.0%
        148bp
        150bp
        20%
        5.7M
        SRR11605266
        92.2%
        92.2%
        1.5%
        SRR11605266_1
        69.4%
        36.0%
        150bp
        150bp
        20%
        7.7M
        SRR11605266_2
        68.0%
        36.0%
        150bp
        150bp
        20%
        7.7M
        SRR11605266_kneaddata_paired_1
        70.4%
        36.0%
        149bp
        150bp
        20%
        7.4M
        SRR11605266_kneaddata_paired_2
        69.3%
        36.0%
        149bp
        150bp
        20%
        7.4M
        SRR11605267
        91.4%
        91.4%
        2.0%
        SRR11605267_1
        61.4%
        40.0%
        150bp
        150bp
        20%
        5.3M
        SRR11605267_2
        48.8%
        40.0%
        150bp
        150bp
        10%
        5.3M
        SRR11605267_kneaddata_paired_1
        60.8%
        39.0%
        149bp
        150bp
        20%
        4.6M
        SRR11605267_kneaddata_paired_2
        53.3%
        39.0%
        145bp
        150bp
        20%
        4.6M
        SRR11605268
        92.4%
        92.5%
        1.0%
        SRR11605268_1
        60.7%
        38.0%
        150bp
        150bp
        20%
        5.3M
        SRR11605268_2
        59.1%
        38.0%
        150bp
        150bp
        20%
        5.3M
        SRR11605268_kneaddata_paired_1
        61.3%
        38.0%
        149bp
        150bp
        20%
        5.0M
        SRR11605268_kneaddata_paired_2
        60.2%
        38.0%
        148bp
        150bp
        20%
        5.0M
        SRR11605269
        77.1%
        77.1%
        3.1%
        SRR11605269_1
        45.2%
        41.0%
        150bp
        150bp
        10%
        4.9M
        SRR11605269_2
        43.8%
        41.0%
        150bp
        150bp
        10%
        4.9M
        SRR11605269_kneaddata_paired_1
        45.5%
        41.0%
        149bp
        150bp
        10%
        4.7M
        SRR11605269_kneaddata_paired_2
        44.4%
        41.0%
        148bp
        150bp
        10%
        4.7M
        SRR11605270
        0.0%
        58.4%
        0.6%
        SRR11605270_1
        35.7%
        45.0%
        150bp
        150bp
        10%
        8.0M
        SRR11605270_2
        33.7%
        45.0%
        150bp
        150bp
        10%
        8.0M
        SRR11605270_kneaddata_paired_1
        35.9%
        45.0%
        149bp
        150bp
        10%
        7.7M
        SRR11605270_kneaddata_paired_2
        34.4%
        45.0%
        148bp
        150bp
        10%
        7.7M
        SRR11605271
        36.5%
        68.2%
        0.7%
        SRR11605271_1
        55.9%
        49.0%
        150bp
        150bp
        30%
        7.3M
        SRR11605271_2
        53.2%
        49.0%
        150bp
        150bp
        30%
        7.3M
        SRR11605271_kneaddata_paired_1
        56.5%
        49.0%
        149bp
        150bp
        30%
        6.9M
        SRR11605271_kneaddata_paired_2
        54.6%
        49.0%
        148bp
        150bp
        30%
        6.9M
        SRR11605272
        88.7%
        88.7%
        0.7%
        SRR11605272_1
        63.6%
        39.0%
        150bp
        150bp
        20%
        7.2M
        SRR11605272_2
        60.8%
        39.0%
        150bp
        150bp
        20%
        7.2M
        SRR11605272_kneaddata_paired_1
        64.3%
        39.0%
        149bp
        150bp
        20%
        6.9M
        SRR11605272_kneaddata_paired_2
        62.2%
        39.0%
        148bp
        150bp
        20%
        6.9M
        SRR11605273
        94.7%
        94.7%
        0.6%
        SRR11605273_1
        70.8%
        39.0%
        150bp
        150bp
        20%
        7.5M
        SRR11605273_2
        69.1%
        39.0%
        150bp
        150bp
        20%
        7.5M
        SRR11605273_kneaddata_paired_1
        71.6%
        39.0%
        149bp
        150bp
        20%
        7.2M
        SRR11605273_kneaddata_paired_2
        70.2%
        39.0%
        149bp
        150bp
        20%
        7.2M
        SRR11605274
        94.0%
        94.0%
        0.6%
        SRR11605274_1
        70.3%
        39.0%
        150bp
        150bp
        20%
        6.3M
        SRR11605274_2
        68.6%
        39.0%
        150bp
        150bp
        20%
        6.3M
        SRR11605274_kneaddata_paired_1
        71.2%
        39.0%
        149bp
        150bp
        20%
        6.1M
        SRR11605274_kneaddata_paired_2
        69.7%
        39.0%
        149bp
        150bp
        20%
        6.1M

        Kraken

        Taxonomic classification using exact k-mer matches to find the lowest common ancestor (LCA) of a given sequence.URL: https://ccb.jhu.edu/software/krakenDOI: 10.1186/gb-2014-15-3-r46

        Top taxa

        The number of reads falling into the top 5 taxa across different ranks.

        To make this plot, the percentage of each sample assigned to a given taxa is summed across all samples. The counts for these top 5 taxa are then plotted for each of the 9 different taxa ranks. The unclassified count is always shown across all taxa ranks.

        The total number of reads is approximated by dividing the number of unclassified reads by the percentage of the library that they account for. Note that this is only an approximation, and that kraken percentages don't always add to exactly 100%.

        The category "Other" shows the difference between the above total read count and the sum of the read counts in the top 5 taxa shown + unclassified. This should cover all taxa not in the top 5, +/- any rounding errors.

        Note that any taxon that does not exactly fit a taxon rank (eg. - or G2) is ignored.

        Created with MultiQC

        FastQC

        Version: 0.12.1

        Quality control tool for high throughput sequencing data.URL: http://www.bioinformatics.babraham.ac.uk/projects/fastqc

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Created with MultiQC

        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Created with MultiQC

        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Created with MultiQC

        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Created with MultiQC

        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Created with MultiQC

        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Created with MultiQC

        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (e.g. PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Created with MultiQC

        Overrepresented sequences by sample

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as overrepresented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        64 samples had less than 1% of reads made up of overrepresented sequences

        Top overrepresented sequences

        Top overrepresented sequences across all samples. The table shows 20 most overrepresented sequences across all samples, ranked by the number of samples they occur in.

        Showing 8/8 rows and 3/3 columns.
        Overrepresented sequenceReportsOccurrences% of all reads
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCATACAATCTCGTAT
        1
        20819
        0.0048%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGACTGGAATCTCGGTT
        1
        12503
        0.0029%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGACTGGAATCTCGGGT
        1
        11895
        0.0028%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACGCCAAGACATCTCGTAT
        1
        10272
        0.0024%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCATACAATCTCGTTT
        1
        9927
        0.0023%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCATACAATCTCGGAT
        1
        8519
        0.0020%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCATACAATCTCGGTT
        1
        5931
        0.0014%
        GATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCATACAATCGCGTAT
        1
        5736
        0.0013%

        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Created with MultiQC

        Status Checks

        Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

        It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

        Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

        In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        FastQC0.12.1